Discovering genomic rearrangements under selection in serious ovarian cancer
Discovering genomic rearrangements under selection in serious ovarian cancer
批准号:
8773658
负责人:
Julia Salzman
金额:
$24.15万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-01-01 至 2016-12-31
关键词:
AccountingAwardBioinformaticsCarcinomaCellsCessation of lifeChromosomal RearrangementClinicalComplexCytogeneticsDNA Sequence RearrangementDataDevelopmentDouble MinutesEarly DiagnosisEarly identificationGene Expression ProfileGene FusionGene RearrangementGenomicsHigh-Throughput Nucleotide SequencingHumanIndividualMalignant NeoplasmsMalignant neoplasm of ovaryMentorsMentorshipMethodsPhaseRNARecurrenceResearch PersonnelSerousStatistical MethodsSymptomsTechniquesTechnologyTestingTrainingTranscriptWomananalytical methodcancer genomecareer developmentdeep sequencingdesignkillingsmolecular markernoveloutcome forecastpressureresearch studysuccesstherapeutic targettumor
中文摘要
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英文摘要
Recurrent gene fusions and internal tandem duplications are among the most tumor-specific molecular
markers known and can provide the potential for therapeutic targets. With a few notable exceptions,
however, relatively common recurrent gene fusions have not been identified in commonly occurring
carcinomas, which often have multiple, complex chromosomal rearrangements that are difficult to analyze by
traditional cytogenetic approaches. Complex tumor karyotpes make it difficult to identify gene fusions using
cytogenetics, but suggest the possibility that recurrent rearrangements producing fusions or internal tandem
duplications (ITDs) may be prevalent. This proposal aims to use deep sequencing and the novel analytic
techniques described to study aspects of the serous ovarian cancer genome and transcriptome which have
remained hidden due to limitations in technology or analytical methods, and to test intra-individual and inter-individual
selective pressures on tumors. The aspects of this proposal are as follows 1) to further investigate
the extent of gene rearrangements in ovarian cancer, focusing on discovering local rearrangements
transcribed into RNA; 2) to determine the composition of a group of novel circular transcripts that I have
recently found to be expressed at relatively high levels in normal and pathogenic human cells; 3) to
characterize double minutes in ovarian cancer, combining bioinformatics to determine rearrangements in
their sequence composition and statistical analysis to determine evolutionary pressures on their composition
exerted by the tumors. The applicant has a track-record of success in discovering novel gene fusions with
ultra-high throughput sequencing (the ESRRA-C11 orf20 fusion), as well as designing original rigorous
statistical and bioinformatic methods for ultra-high throughput data. Under the mentorship of Dr. Patrick O. Brown, a pioneer in high throughput genomic technologies and statistical methods for analyzing them, the applicant will continue career development and training. The first aim of this project will be performed during the mentoring phase, and experiments for aims 2 and 3 will be piloted. The K99/R00 award will support the applicant in her development into an independent investigator.
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依托单位:
海外基金